<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The paper considers the use of the bootstrap method to improve the determination of confidence intervals identified by the DOE (design of experiment) procedure. Two different approaches have been used: one that is appropriate for factorial designs and the other one relevant to the methodology of the response surface. Both approaches were tested on the real experiment datasets and compared with the results obtained from the classical statistical expressions based on well-known asymptotic formulas derived from the <italic>t</italic> distribution.</p>
</abstract>

The paper considers the use of the bootstrap method to improve the determination of confidence intervals identified by the DOE (design of experiment) procedure. Two different approaches have been used: one that is appropriate for factorial designs and the other one relevant to the methodology of the response surface. Both approaches were tested on the real experiment datasets and compared with the results obtained from the classical statistical expressions based on well-known asymptotic formulas derived from the t distribution.

The Bootstrap Method As A Tool To Improve The Design Of Experiments

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This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"The Bootstrap Method As A Tool To Improve The Design Of Experiments"}

The paper considers the use of the bootstrap method to improve the determination of confidence intervals identified by the DOE (design of experiment)...

The Bootstrap Method As A Tool To Improve The Design Of Experiments

Publié en ligne: 28 mars 2019

Pages: 724 - 729

Reçu: 30 nov. 2018

Accepté: 05 févr. 2019

DOI: https://doi.org/10.2478/czoto-2019-0092

Mots clés
bootstrap, statistics, design of experiments, numerical simulation

© 2019 Renata Dwornicka et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

The Bootstrap Method As A Tool To Improve The Design Of Experiments

Publié en ligne: 28 mars 2019

Pages: 724 - 729

Reçu: 30 nov. 2018

Accepté: 05 févr. 2019

DOI: https://doi.org/10.2478/czoto-2019-0092

Mots clésbootstrap, statistics, design of experiments, numerical simulation

© 2019 Renata Dwornicka et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Mots clés
bootstrap, statistics, design of experiments, numerical simulation